Thursday, 29 September 2022

e-resources on building-blocks of statistical analysis for research project

 e-resources on building-blocks of statistical analysis for research project

Basic concepts for revision

a. Descriptive Statistics, Part 1

b. Descriptive Statistics, Part 2

c. Descriptive vs Inferential Statistics


I. Building blocks at the initial stage:

constructs.

conceptual definitions.

operational definitions.

* variables and operationalization in quantitative methods.

conceptualization and operationalization.

theories and operational definitions.

* Data types

true, quasi, pre, and non-experiment.

density curves and their properties.

on variables.

Some different types of relationships

on mediator and moderator variables. (also watch mediation, moderation and the third variable problem). [again on Regression: Mediator vs. Moderator]

steps to formulate a strong hypothesis.

Why did I get null results?

on falsification.

on standard normal distribution.

the normal distribution rule.

normal distribution explained - part 1.

normal distribution explained - part 2.

understanding the central limit theorem.

* On statistical significance.

* On confidence and significance level

P-values and critical values.

on one tail and two tail tests.

Representative vs Biased Samples

* On sampling in research methods study.

II. Specific statistical techniques

Technique 1: chi-squared test

simple explanation of chi-squared test.

chi-square distribution.

a briefing on chi-squared test.

An illustration of calculating p-value for ch-squared test with Excel.

a tutorial on the chi-squared test.

chi square distribution.

Technique 2: Excel pivot table

on multidimensional data analysis - a conceptual note. [about using Excel pivot table].

using Excel pivot table to study homelessness.

Videos: (1) how to create pivot tables. (2) pivot table tutorial.

Also see blog note on pivot table as a research tool.


Technique 3: correlation analysis

* Linear equation: introduction.

understanding correlation. (also on the basic steps to calculate correlation coefficient).

an introduction to linear regression analysis.

introduction to simple linear regression. (also take a look at linear vs exponential for some clarification of the linear concept).

* How to calculate linear regression using least square method.

what are correlations?

Correlation and causation (also study causal inference and causality).

correlation vs regression.

coefficient of determination. (r squared). (on how to calculate r squared).

correlation coefficient. (also on calculating r and r squared).

* on standard error of the estimate in regression analysis. (more importantly on SSE, SSR, SST and R-squared)

* (i) Excel scatter diagram and calculation of coefficient of correlation (r). And then on showing (ii) trend [regression] line and the linear equation (also coefficient of correlation). This one is on the regression line and show more equation info on the line

multiple linear regression. part 1

multiple linear regression part 2.

multiple linear regression - evaluating basic models.

* Correlational research design. [another one on the same topic]

* Correlation hypothesis testing.

* on control variables; mediator and moderator. (further discussion on mediator under the topic of intervening variable).

Comparing Descriptive, Correlational, and Experimental Studies

using Excel for multiple regression analysis./ Excel 2016 regression analysis.  Another video on demonstration (covering how to add on the function of regression analysis)

* interpreting Excel regression report: video 1; video 2; note the info on "adjusted R square" and the meaning of the major figures of the report.

** note that in Excel regression report, the p-value is a measure on 1 corner of the p-value curve; for a two-tailed test, the alpha value is (5%/2 = 2.5%). In this case the p-value is to be compared with 2.5% (for a two-tailed test).



*** also study this blog note related to correlation.


Technique 4: ANOVA

one-way ANOVA with Excel.

basic ideas on one-way ANOVA.

* Introduction to the F-statistic.

one-way ANOVA with manual calculation. [also take a look at the F-value calculator and a video on F-test calculation]

* A note on explanation of F-value.

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